Training Rapid Stepping Responses in an Individual With Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Compensatory stepping reactions are important responses to prevent a fall following a postural perturbation. People with hemiparesis following a stroke show delayed initiation and execution of stepping reactions and often are found to be unable to initiate these steps with the more-affected limb. This case report describes a targeted training program involving repeated postural perturbations to improve control of compensatory stepping in an individual with stroke. CASE DESCRIPTION: Compensatory stepping reactions of a 68-year-old man were examined 52 days after left hemorrhagic stroke. He required assistance to prevent a fall in all trials administered during his initial examination because he showed weight-bearing asymmetry (with more weight borne on the more-affected right side), was unable to initiate stepping with the right leg (despite blocking of the left leg in some trials), and demonstrated delayed response times. The patient completed 6 perturbation training sessions (30-60 minutes per session) that aimed to improve preperturbation weight-bearing symmetry, to encourage stepping with the right limb, and to reduce step initiation and completion times. OUTCOMES: Improved efficacy of compensatory stepping reactions with training and reduced reliance on assistance to prevent falling were observed. Improvements were noted in perturbation asymmetry and step timing. Blocking the left foot was effective in encouraging stepping with the more-affected right foot. DISCUSSION: This case report demonstrates potential short-term adaptations in compensatory stepping reactions following perturbation training in an individual with stroke. Future work should investigate the links between improved compensatory step characteristics and fall risk in this vulnerable population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".